Practice : Linting and Static Code Analysis

Purpose and Strategic Importance

Linting and Static Code Analysis help maintain high code quality and security by automatically identifying issues in source code without executing it. These tools catch bugs, enforce coding standards, and prevent vulnerabilities early in the development lifecycle.

By integrating these checks into daily workflows and CI/CD pipelines, teams build more reliable, maintainable, and secure software - while reducing review burden and technical debt.

Description of the Practice

  • Linters detect style, syntax, and formatting issues based on rulesets (e.g. ESLint, Stylelint, Flake8).
  • Static Analysis Tools analyse code structure for logic errors, bugs, smells, and security flaws (e.g. SonarQube, CodeQL, Semgrep).
  • Tools are integrated into editors, pre-commit hooks, and CI/CD pipelines.
  • Reports are visible in pull requests, dashboards, or IDEs for quick feedback.
  • Rules can be customised to balance team conventions and compliance needs.

How to Practise It (Playbook)

1. Getting Started

  • Choose language-appropriate linters and static analysis tools.
  • Integrate them into your editor (e.g. VSCode), pre-commit hooks, and CI pipelines.
  • Use baseline rulesets, then refine based on your team’s standards and risk profile.
  • Visualise findings and address key issues during code reviews or retros.

2. Scaling and Maturing

  • Define quality gates in CI to prevent merging high-severity issues.
  • Tune rules to reflect domain-specific best practices.
  • Track trends in technical debt and maintainability over time.
  • Add security rules for vulnerability patterns and OWASP Top 10 issues.
  • Pair static analysis with mutation testing and coverage metrics.

3. Team Behaviours to Encourage

  • Treat static analysis feedback as part of development - not just release prep.
  • Use findings to coach new team members on coding standards.
  • Celebrate improvements in maintainability and defect reduction.
  • Review and adapt rule configurations regularly as your stack evolves.

4. Watch Out For…

  • Too many rules or overly strict policies that slow teams down.
  • High false positive rates leading to ignored alerts.
  • Static analysis being treated as “someone else’s job” - it’s a shared responsibility.
  • Tooling drift where dev and CI configurations fall out of sync.

5. Signals of Success

  • Code issues are identified and resolved before pull request reviews.
  • Defect rates and rework decrease over time.
  • Static analysis metrics are visible and acted on regularly.
  • Teams see feedback as helpful, not punitive.
  • Codebases remain consistent, secure, and maintainable at scale.